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Magnetographic Diagnostics of Heart Diseases

Object of Investigation

Considering medical studies, many of the Human organs, such as the heart, are sources of a weak pulsating magnetic fields. If measured accurately, these fields can be used to diagnose heart diseases similar to conventional an electrocardiograph, that uses electric potentials on the Human body surface.

A database was created (by GE) to construct magnetographic diagnostic rules. The study compiled measurements on 63 patients: 15 with the myocardial infarction, 16 with the ventricular tachycardia and 32 normal people. For every patient, 56 magnetometric sensor points were measured and every signal was digitized with a frequency of 500 Hz.

Primary Goals

The research goal to formulate diagnostic rules was to distinguish between myocardial infarction, ventricular tachycardia and normal cases. The comparative analysis between a magnetograph and electrocardiograph was also a primary goals.


The database contained 68,000 variables that were considerably noised and possibly a non-linear decision rule, made the problem analytically complex. To achieve information on these questions would have more value than using an analytical technique.

The Result

The discrimination rules for diagnostics in two types of diseases were formulated in magnetographic and electrographic data sets. KET demonstrated that the potential of magnetographic measurements revealed the diagnostic success was due to the preservation of important high frequency components in magnetographic signals. Additionally, the newly discovered electrocariographic rules produced more accurate results than conventional routines.


Increase diagnostic reliability in the new sources was found in both conventional EKG measurements and magnetographic signals. The difference between myocardial infarction and ventricular tachycardia cases was the diagnostic errors were reduced from 16% to 2%. Recommendations to improve the data collection process was suggested.

How it was Done

A combination of the Information Analysis and Fourier Analysis Modules were used to reduced the data set. The results in this stage suggested a special non-linear data converter design that would compress the original database from 68,000 to 112 variables. The Generator of Discrimination Rules was used in the construction the diagnostic routines. Finally, the Optimization Modules of KET were applied to optimize the rules to achieve the finest diagnostic's quality.


The continuation of this research would allow to created a commercial diagnostic system combining advantages of both types of data: EKG and MKG.

  New Feature !!

A new KET module was introduced recently to support interaction with "Mathematica 8" system.


  News !!

KET, LLC joined BioMed Content Group, Inc. in initiative of using AI agents to facilitate work of physicians and educators.

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